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Bacteriology unlocks mastitis-treatment benefits (Nov/Dec 24)

On-farm bacteriology is the key to improving the efficiency of antibiotic use and the effective treatment of clinical and sub-clinical mastitis. We spoke to a vet to find out more.


TEXT PHIL EADES



Clinical mastitis continues to be one of the main health challenges facing dairy herds, accounting for a significant proportion of antibiotic use on farm. And new data highlights that in many cases antibiotic treatment is unnecessary.


Kingshay’s 2024 Dairy Costings Focus Report showed the average incidence of clinical mastitis in UK herds is 26 cases per 100 cows, down from 29 cases in 2023. Clinical mastitis still costs around £8,100 per 100 cows per year and accounts for 8% of all culls. Kingshay also reported a significant reduction in the use of antibiotics, although the rate of decline has plateaued during the past two years.


Vet Georgia Thresh, from Wood Veterinary Group, is also a technical adviser at Agsenze and she says new technologies can increase the precision of diagnosis and treatment, reducing the incidence and cost of clinical mastitis and the use of antibiotics.


“All herds should aim to reduce the incidence of clinical mastitis while also continuing to review whether antibiotic treatment is necessary, both for clinical and subclinical cases,” she says. “This is where on-farm bacteriology is a useful tool, supporting improved decision-making and reducing unnecessary and inappropriate use of antibiotics.”


She stresses that understanding the bacterial cause of a mastitis case, and the antibiotic sensitivity of the bacteria present, are key information for informing treatment decisions. “Gram-negative and gram-positive bacteria strains respond differently to antibiotic treatments. A significant proportion of mastitis cases on many UK farms are caused by E coli or other gram-negative pathogens or have no identified bacterial cause.”


Unnecessary treatment


Treating these cases with antibiotics is often unnecessary because, typically, they tend to respond poorly to the antibiotics routinely used and will respond to oral and/ or IV fluids and non-steroidal anti-inflammatory drugs (NSAIDs) alone. “But the lack of timely bacteriology information, means antibiotics are used unnecessarily in many cases,” says Ms Thresh.


“For cows with a gram-positive mastitis infection, such as Strep uberis or Staph aureus, understanding antibiotic sensitivity can improve cure rates, because it allows the herd’s vet to make better-informed decisions about the most effective antibiotic treatment protocol for each case. This is why greater use of bacteriology can offer such significant benefits.”


An analysis of clinical mastitis samples bacteriologically tested by Mastatest in 2024, and compared to a similar analysis of samples tested in 2023, was shared with delegates at this year’s British Mastitis Conference. The data, from 4,590 UK herd clinical samples, demonstrates potential for on-farm bacteriology to improve precision with mastitis treatment protocols. This results in improved cure rates, reduces antibiotic use, and offers treatment and performance cost savings.


Figure 1 shows the number of cases analysed with pathogen-type breakdown, comparing 2023 and 2024 results. In 12% of cases no bacteria were detected. In 26% of cases, the causal bacteria were E coli or other gram-negative strains, and 2% showed Klebsiella and Serratia strains.


Cost savings


“Taken together, these results show that up to 40% of all the samples could be assumed to not benefit from antibiotics, allowing direct and indirect treatment cost savings and antibiotic usage to be safely reduced,” says Ms Thresh.


“Antibiotic sensitivity testing also confirmed that in the vast majority of the E coli cases there was a low chance of the animal responding to antibiotics typically prescribed to UK herds. For the other bacteria types identified, there was a range of antibiotic sensitivity profiles which has important practical implications.


“These results underline that there is no ‘one size fits all’ approach to antibiotic selection for maximum efficacy. There were markedly different sensitivities for different Strep Uberis and other Strep species. Using a less effective treatment protocol will mean the cow takes longer to recover,” she adds.


“The key to reducing antibiotic use is rapid bacteriology so treatment protocols can be refined and their efficacy improved.”


Bacteriology has been a time-consuming process in the past, requiring samples to be sent away for testing and with results often back on farm too late to allow better decisions to be made at an individual-cow level.


On-farm test: kit is quick and easy to use


The Mastatest on-farm system, distributed by Agsenze, overcomes these pitfalls and allows a sample to be tested with data back on-farm rapidly, allowing prompt and accurate treatment decisions.


The test automatically processes milk samples using a cartridge system, and an electronic eye that takes images of the samples as time passes. The images are sent to the Cloud, where they are analysed and interpreted, with results in producers’ and vets’ inboxes within 24 hours. The results show the type of bacteria present or confirmation of no bacteria being present, and the bacterial sensitivity to commonly-used antibiotics. Data is used to generate a recommended treatment plan, based on a protocol previously devised by the herd’s vet.


Ms Thresh says that, on many units, Mastatest is an effective way of unlocking the benefits of bacteriology for mastitis treatment. The improved practicality, cost, and time savings will remove the barrier to engaging with pathogen testing for some producers who are not yet engaged in the benefits of bacteriology testing.


“The data collected builds a comprehensive picture of udder health for the herd, demonstrating the specific pathogen breakdown for mastitis cases. The data is collated in a clear way at both individual-cow and herd level,” she explains.


Prevention strategies


This herd-level data is invaluable when considering mastitis prevention strategies. Choosing the optimal prevention strategies is key but can be costly. Having the benefit of a large dataset of pathogen type, alongside trends in cell counts and clinical mastitis cases, allows vets to advise on the most effective prevention strategies for that herd, maximising the return on investment for the spend on mastitis prevention.


Ms Thresh adds that the data clearly show that bacterial identification, used alongside antibiotic sensitivity, gives producers and their vets unique, detailed insights into mastitis infection in the herd that, in turn, can provide the base for more effective treatments.


“Based on this data, the average UK herd could reduce antibiotic use by up to 40% using Mastatest for clinical cases alone. While in the other cases more effective antibiotic selection will help reduce the consequential losses of infections.”


In addition to offering the ability to quickly identify the bacterial cause of clinical mastitis cases, Mastatest also includes a sub-clinical case test cartridge. This means that producers can test cows with high cell counts, either at the point of drying off when making selective-dry-cow-therapy decisions, or during lactation to potentially inform treatment. Using pathogen information alongside other history factors helps determine whether treatment of high-cell-count cases may be warranted or effective in reducing the risk of cows becoming high-cell-count carriers.


A significant proportion of the average cost per case (£314) reported by Kingshay is made up of antibiotics and milk disposal. “If 40% of cases require no antibiotics, then the cost per case can be reduced while at the same time helping achieve the targets for reduced antibiotic use on UK units,” says Ms Thresh.


“Timely bacterial identification combined with antibiotic sensitivity information will offer producers and their vets a detailed insight into the cause of infection, enabling more effective treatment and prevention protocols at both the individual cow and herd level.”

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